AI Product Engineer

What you'll do

• Build infrastructure including extraction scripts, validation frameworks, and integration connectors to make AI tools production-ready.
• Develop logic to ensure consistent output quality and handle recovery when AI models produce unexpected results.
• Integrate AI solutions into the enterprise environment using REST APIs, Microsoft Graph, SharePoint, and OneDrive.
• Design multi-step reasoning pipelines and agentic workflows using Model Context Protocol and similar infrastructures.
• Establish engineering standards for packaging, versioning, configuration management, and error handling across the AI portfolio.
• Create internal tools to accelerate the development of new AI solutions while maintaining codebase scalability.
• Manage complex data processing tasks including document parsing, schema validation, and RAG implementation.
• Develop test infrastructure and evaluation frameworks to monitor performance for systems with probabilistic outputs.

What we're looking for

• Strong Python proficiency including data parsing, file I/O, schema validation, and test authoring (preferred).
• Solid understanding of REST API design, consumption, authentication patterns, and error handling (preferred).
• Experience with document parsing libraries such as PyMuPDF, python-docx, openpyxl, and pandas (preferred).
• Proficiency in Git-based development workflows including branching, versioning, and code review (preferred).
• Familiarity with Microsoft 365 integration surfaces like SharePoint, OneDrive, and Graph API (preferred).
• Experience building the code layer around LLM APIs, including prompt engineering and output validation (preferred).
• Knowledge of RAG patterns, agentic workflows, and multi-step reasoning pipelines (preferred).